Ali Sadaqat, Noreen Asifa, Qamar Adeem, Zafar Imran, Ain Quratul, Nafidi Hiba-Allah, Bin Jardan Yousef A, Bourhia Mohammed, Rashid Summya, Sharma Rohit
Medical Department, DHQ Hospital Bhawalnagr, Punjab, Pakistan.
Department of Chemistry, Rippha International University, Faisalabad, Pakistan.
Front Chem. 2023 Apr 26;11:1174363. doi: 10.3389/fchem.2023.1174363. eCollection 2023.
Cancer is a primary global health concern, and researchers seek innovative approaches to combat the disease. Clinical bioinformatics and high-throughput proteomics technologies provide powerful tools to explore cancer biology. Medicinal plants are considered effective therapeutic agents, and computer-aided drug design (CAAD) is used to identify novel drug candidates from plant extracts. The tumour suppressor protein TP53 is an attractive target for drug development, given its crucial role in cancer pathogenesis. This study used a dried extract of seeds to identify phytocompounds targeting TP53 in cancer. We apply qualitative tests to determine its phytochemicals (Alkaloid, Tannin, Saponin, Phlobatinin, and Cardic glycoside), and found that alkaloid composed of 9.4% ± 0.04% and Saponin 1.9% ± 0.05% crude chemical constituent. In the results of DPPH Analysis Seeds founded antioxidant activity, and then we verified via observing methanol extract (79.82%), BHT (81.73%), and n-hexane extract (51.31%) found to be positive. For Inhibition of oxidation, we observe BHT is 90.25%, and Methanol (83.42%) has the most significant proportion of linoleic acid oxidation suppression. We used diverse bioinformatics approaches to evaluate the effect of seeds and their natural components on TP53. Compound-1 had the best pharmacophore match value (53.92), with others ranging from 50.75 to 53.92. Our docking result shows the top three natural compounds had the highest binding energies (-11.10 to -10.3 kcal/mol). The highest binding energies (-10.9 to -9.2 kcal/mol) compound bonded to significant sections in the target protein's active domains with TP53. Based on virtual screening, we select top phytocompounds for targets which highly fit based on pharmacophore score and observe these compounds exhibited potent antioxidant activity and inhibited cancer cell inflammation in the TP53 pathway. Molecular Dynamics (MD) simulations indicated that the ligand was bound to the protein with some significant conformational changes in the protein structure. This study provides novel insights into the development of innovative drugs for the treatment of cancer disorders.
癌症是全球主要的健康问题，研究人员在寻找对抗该疾病的创新方法。临床生物信息学和高通量蛋白质组学技术为探索癌症生物学提供了强大工具。药用植物被认为是有效的治疗剂，计算机辅助药物设计（CAAD）用于从植物提取物中识别新型候选药物。鉴于肿瘤抑制蛋白TP53在癌症发病机制中的关键作用，它是药物开发的一个有吸引力的靶点。本研究使用种子的干燥提取物来鉴定癌症中靶向TP53的植物化合物。我们应用定性测试来确定其植物化学成分（生物碱、单宁、皂苷、根皮苷和强心苷），发现生物碱占粗化学成分的9.4%±0.04%，皂苷占1.9%±0.05%。在DPPH分析结果中，种子具有抗氧化活性，然后我们通过观察发现甲醇提取物（79.82%）、BHT（81.73%）和正己烷提取物（51.31%）呈阳性。对于氧化抑制，我们观察到BHT为90.25%，甲醇（83.42%）对亚油酸氧化抑制的比例最高。我们使用多种生物信息学方法来评估种子及其天然成分对TP53的影响。化合物-1具有最佳的药效团匹配值（53.92），其他值在50.75至53.92之间。我们的对接结果显示，排名前三的天然化合物具有最高的结合能（-11.10至-10.3千卡/摩尔）。结合能最高（-10.9至-9.2千卡/摩尔）的化合物与TP53靶蛋白活性域中的重要区域结合。基于虚拟筛选，我们根据药效团得分选择高度匹配靶点的顶级植物化合物，并观察到这些化合物表现出强大的抗氧化活性并抑制TP53途径中的癌细胞炎症。分子动力学（MD）模拟表明，配体与蛋白质结合，蛋白质结构发生了一些显著的构象变化。本研究为开发治疗癌症疾病的创新药物提供了新的见解。
